Every story in this issue with a short summary, so you can decide what to read before leaving the site. Summaries are written by AI (Claude) only from each publisher's own description and checked by Jev for anything not in that description. They are not full translations. Follow "Read the original" for the full story.
The veterinary artificial intelligence market is likely to grow at a 18.8% CAGR during the forecast period for 2026 to 2035. Diagnostic imaging AI is expected to be a major segment driving the market. It is supported by growing adoption of AI-powered radiography analysis, automated image interpretation, and diagnostic assistance in veterinary practices.
Read the original →Using AI to analyze data from a portable cuff-based blood pressure monitor and a wrist-worn device may help identify adults with stage 2 high blood pressure who are at increased risk of a hypertensive crisis up to three days before it occurs. The independent, preliminary research is to be presented at the American Heart Association's Scientific Sessions 2026.
Read the original →The agentic AI in healthcare market is projected to grow from $1,030.95 million in 2026 to $14,010.89 million by 2034. This represents a CAGR of 38.56% during the forecast period 2026-2034.
Read the original →A conference in Manipal discussed AI wastewater testing to detect early pandemic threats. Questions raised included whether signs of a new pandemic can be detected before it spreads, and whether data from different hospitals, laboratories and health agencies can be integrated to identify infection risk in time.
Read the original →Dr. Kunle Ashimi, former Chairman of the Nigerian Medical Association's Ogun State Branch, called for the adoption of AI and telemedicine to address healthcare challenges in Africa. He cited the shortage of medical personnel and limited access to specialist services in rural communities.
Read the original →Stony Brook University researchers found that doctors preferred AI-generated discharge summaries in 95% of 60 assessed internal medicine hospitalizations.
Read the original →LeanTaaS is acquiring LookDeep Health to launch iQueue for Virtual Care. The product embeds ambient computer vision into enterprise capacity management and is described as cutting falls by 70%.
Read the original →Shyld AI is a Silicon Valley based AI company. The announcement was issued from Sunnyvale, California, on Nov. 02, 2026.
Read the original →Daphne Koller agrees with Bruce Booth that AI molecular design will worsen pharma R&D productivity before improving it. The piece discusses what the industry must fix first.
Read the original →3billion will showcase its Genetics-First AI Drug Discovery strategy and pipeline at BIO-Europe 2026. The presentation will highlight patient genomic data, proprietary AI technologies, and drug discovery programs in oncology and immunology.
Read the original →Patients, providers and medtech firms submitted hundreds of comments to the Food and Drug Administration on how the agency should approach generative AI in medical devices.
Read the original →The European lower mid market covers healthcare technology, MedTech and clinical AI enterprises with revenue of €5 million to €50 million, enterprise values of €25 million to €250 million, and operating EBITDA of €1 million to €10 million. It is entering a distinct developmental cycle. This follows the contraction of venture-backed expansion that characterised 2022 through 2024.
Read the original →The announcement concerns the 2026 World Internet Conference on November 2, with Ant Group named in the description.
Read the original →A six-week randomized trial of 1,137 students found that the Flourish app improves stress, depression, and anxiety outcomes.
Read the original →A study finds that the AI's measurements predict mortality risk better than those of medical staff. The reported error rate is 1%.
Read the original →Deloitte Tohmatsu found that a majority of doctors in Japan use generative AI to gather information when selecting patient treatments. Use is especially common in cancer, where much information is needed to decide on treatment. The survey covered 561 doctors at Japanese medical institutions in March, evenly spread across six fields including lifestyle-related diseases and solid cancers. The type of generative AI used was not examined.
Read the original →A study found that AI can analyze heart MRI scans much faster than doctors and predict patients' mortality risk more accurately. The research was a joint effort by City St George's, University of London and University College London (UCL).
Read the original →Artificial intelligence is bringing change to drug discovery and medical care, with results such as early cancer detection and shorter drug development times through analysis of large data sets. Creating new knowledge that goes beyond existing findings is described as difficult.
Read the original →AI is very useful for reading CT and MRI scans, prescribing medication and detecting medical errors. The article says it is important to maintain the principle that AI is not the author of diagnostic results. Authorship of AI-supported diagnoses must belong to the doctor.
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